Search Results - (( java application graph algorithm ) OR ( _ normalization mining algorithm ))
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Ant colony optimization algorithm for load balancing in grid computing
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A Text Mining Algorithm Optimising the Determination of Relevant Studies
Published 2023Conference Paper -
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Dynamic force-directed graph with weighted nodes for scholar network visualization
Published 2022“…The approach is realized by creating a web-based interface using D3 JavaScript algorithm that allows the visualization to focus on how data are connected to each other more accurately than the conventional lines of data seen in traditional data representation. …”
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Frequent Lexicographic Algorithm for Mining Association Rules
Published 2005“…The scale-up experiment showed that the proposed algorithm is more scalable than the other existing algorithms. …”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price
Published 2014“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Improved normalization and standardization techniques for higher purity in K-means clustering
Published 2016“…Clustering is an unsupervised classification method with aim of partitioning, where objects in the same cluster are similar, and objects belong to different clusters vary significantly, with respect to their attributes. The K-means algorithm is a famous and fast technique in non-hierarchical cluster algorithms. …”
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Data mining in network traffic using fuzzy clustering
Published 2003Get full text
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Data mining in network traffic using fuzzy clustering
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Effective mining on large databases for intrusion detection
Published 2014“…Data mining is a common automated way of generating normal patterns for intrusion detection systems. …”
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An enhancement of classification technique based on rough set theory for intrusion detection system application
Published 2019“…Thus, to deal with huge dataset, data mining technique can be improved by introducing discretization algorithm to increase classification performance. …”
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Concept Based Lattice Mining (CBLM) using Formal Concept Analysis (FCA) for text mining
Published 2019“…The focus of this study is on the method of Concept Based Lattice Mining (CBLM) where similarities among output lattices will be compared using their normalized adjacency matrices, utilizing a distance measure technique. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis
Published 2016“…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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Prediction Of Leaf Mechanical Properties Based On Geometry Features With Data Mining
Published 2019“…Findings showed that the numerical predictions on FT and ST (RRSE ~ 25%) were about two folds better than the WT and SWT (RRSE ~50%) in the six algorithms tested. The best prediction performance was gained on FT indicator using the M5P algorithm (RRSE = 22.44%). …”
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Concept Based Lattice Mining (CLBM) Using Formal Concept Analysis (FCA) for Text Mining
Published 2019“…The focus of this study is on the method of Concept Based Lattice Mining (CBLM) where similarities among output lattices will be compared using their normalized adjacency matrices, utilizing a distance measure technique. …”
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An initial state of design and development of intelligent knowledge discovery system for stock exchange database
Published 2004“…We divide our problem in two modules.In first module we define Fuzzy Rule Base System to determined vague information in stock exchange databases.After normalizing massive amount of data we will apply our proposed approach, Mining Frequent Patterns with Neural Networks.Future prediction (e.g., political condition, corporation factors, macro economy factors, and psychological factors of investors) perform an important rule in Stock Exchange, so in our prediction model we will be able to predict results more precisely.In second module we will generate clustering algorithm. …”
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Predicting students’ STEM academic performance in Malaysian secondary schools using educational data mining
Published 2023“…CRISP is a cross-industry standard data mining process which consists of six stages of the normal lifecycle of a CRISP-DM project. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets
Published 2019“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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